Adaptive food price forecasting improves public information in times of rapid economic change
Abstract The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010–2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023,...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61660-x |
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| author | Matthew J. MacLachlan Michael K. Adjemian Xiaoli Etienne Megan Sweitzer Richard Volpe III Wendy Zeng |
| author_facet | Matthew J. MacLachlan Michael K. Adjemian Xiaoli Etienne Megan Sweitzer Richard Volpe III Wendy Zeng |
| author_sort | Matthew J. MacLachlan |
| collection | DOAJ |
| description | Abstract The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010–2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023, U.S. Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts using statistical learning protocols to select time series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these “adaptive” inflation forecasts and enhance them by incorporating exogenous variables to improve their precision and explanatory power. COVID-19’s arrival highlighted the value of adapting to the growing relevance of the all-items-less-food-and-energy ("core”) index, the money supply, and wages in predicting food prices. The strong relationships between food prices and core prices and the money supply indicate the sensitivity of food markets to macroeconomic forces and government policy decisions. |
| format | Article |
| id | doaj-art-e22f6cfaa5b44970b1f5c927f5200b88 |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-e22f6cfaa5b44970b1f5c927f5200b882025-08-20T03:05:05ZengNature PortfolioNature Communications2041-17232025-07-0116111410.1038/s41467-025-61660-xAdaptive food price forecasting improves public information in times of rapid economic changeMatthew J. MacLachlan0Michael K. Adjemian1Xiaoli Etienne2Megan Sweitzer3Richard Volpe III4Wendy Zeng5Department of Population Medicine and Diagnostic Sciences, Cornell UniversityDepartment of Agricultural and Applied Economics, University of GeorgiaDepartment of Agricultural Economics and Rural Sociology, University of IdahoFood Economics Division, U.S. Department of Agriculture - Economic Research ServiceAgribusiness Department, California Polytechnic State UniversityMarkets and Trade Economics Division, U.S. Department of Agriculture - Economic Research ServiceAbstract The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010–2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023, U.S. Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts using statistical learning protocols to select time series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these “adaptive” inflation forecasts and enhance them by incorporating exogenous variables to improve their precision and explanatory power. COVID-19’s arrival highlighted the value of adapting to the growing relevance of the all-items-less-food-and-energy ("core”) index, the money supply, and wages in predicting food prices. The strong relationships between food prices and core prices and the money supply indicate the sensitivity of food markets to macroeconomic forces and government policy decisions.https://doi.org/10.1038/s41467-025-61660-x |
| spellingShingle | Matthew J. MacLachlan Michael K. Adjemian Xiaoli Etienne Megan Sweitzer Richard Volpe III Wendy Zeng Adaptive food price forecasting improves public information in times of rapid economic change Nature Communications |
| title | Adaptive food price forecasting improves public information in times of rapid economic change |
| title_full | Adaptive food price forecasting improves public information in times of rapid economic change |
| title_fullStr | Adaptive food price forecasting improves public information in times of rapid economic change |
| title_full_unstemmed | Adaptive food price forecasting improves public information in times of rapid economic change |
| title_short | Adaptive food price forecasting improves public information in times of rapid economic change |
| title_sort | adaptive food price forecasting improves public information in times of rapid economic change |
| url | https://doi.org/10.1038/s41467-025-61660-x |
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